parse_as_geo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "import collections\n",
    "import csv,re,sys,os\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from pandas.io import wb\n",
    "import locale\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'svg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "locale.setlocale(locale.LC_ALL, 'en_US.utf8')\n",
    "\n",
    "def replaceThousands(n):\n",
    "    '''Format large numbers'''\n",
    "    return locale.format(\"%d\",n, grouping=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sns.set_context('paper')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def setFigSize(dim=(16.5,5.5)):\n",
    "    fig = matplotlib.pyplot.gcf()\n",
    "    fig.set_size_inches(dim[0],dim[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Grab CAIDA AS Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "if not os.path.exists('../data'):\n",
    "    os.mkdir('../data')\n",
    "\n",
    "if not os.path.exists('../data/midar-iff.nodes.geo'):\n",
    "    !wget http://data.caida.org/datasets/topology/ark/ipv4/itdk/2013-04/kapar-midar-iff.nodes.geo.gz && \\\n",
    "        gunzip ../data/midar-iff.nodes.geo.gz\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "if False:\n",
    "    !grep -v '#' midar-iff.nodes.geo | awk -F '\\t' '{print $1\"\\t\"$3}' > midar-iff.nodes.geo_reduced\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Read in Geolocated AS Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df=pd.read_csv('../data/midar-iff.nodes.geo_reduced',quotechar='#',delimiter='\\t',header=False,names=['id','country'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(31788985, 2)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Get Country Names and ISO Codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "iso=wb.get_countries()\n",
    "# 'name','iso2c'\n",
    "iso.incomeLevel=iso.incomeLevel.apply(lambda x: re.sub(r'High income: nonOECD|High income: OECD','High income',x))\n",
    "# Collpase OECD and non OECD high income countries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Get Populations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "popDf=wb.download(indicator='SP.POP.TOTL',start=2013,end=2013,country=[v for v in iso.iso2c.values if v])\n",
    "\n",
    "popDf.index=popDf.index.reorder_levels([1,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "popDf=popDf.unstack(level=0)\n",
    "#popDf['iso']=[v for v in iso.iso2c.values if v]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "'''popVals=[]\n",
    "countries=[]\n",
    "for row in popDf.iterrows():\n",
    "#    print row[0][1]\n",
    "#    print row[1]['SP.POP.TOTL']\n",
    "    popVals.append(row[1]['SP.POP.TOTL'])\n",
    "    countries.append(row[0][1])\n",
    "popDf=pd.DataFrame(data={'pop':popVals},index=countries)\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>SP.POP.TOTL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>30551674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>2897366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>39208194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</th>\n",
       "      <td>55165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>79218</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               SP.POP.TOTL\n",
       "year                  2013\n",
       "country                   \n",
       "Afghanistan       30551674\n",
       "Albania            2897366\n",
       "Algeria           39208194\n",
       "American Samoa       55165\n",
       "Andorra              79218"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popDf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "iso.index=iso.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "iso=iso.join(popDf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "iso=iso[~(iso.incomeLevel==\"Aggregates\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>adminregion</th>\n",
       "      <th>capitalCity</th>\n",
       "      <th>iso3c</th>\n",
       "      <th>incomeLevel</th>\n",
       "      <th>iso2c</th>\n",
       "      <th>latitude</th>\n",
       "      <th>lendingType</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>region</th>\n",
       "      <th>(SP.POP.TOTL, 2013)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Aruba</th>\n",
       "      <td></td>\n",
       "      <td>Oranjestad</td>\n",
       "      <td>ABW</td>\n",
       "      <td>High income</td>\n",
       "      <td>AW</td>\n",
       "      <td>12.5167</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>-70.0167</td>\n",
       "      <td>Aruba</td>\n",
       "      <td>Latin America &amp; Caribbean (all income levels)</td>\n",
       "      <td>102911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>South Asia</td>\n",
       "      <td>Kabul</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Low income</td>\n",
       "      <td>AF</td>\n",
       "      <td>34.5228</td>\n",
       "      <td>IDA</td>\n",
       "      <td>69.1761</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>30551674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>Sub-Saharan Africa (developing only)</td>\n",
       "      <td>Luanda</td>\n",
       "      <td>AGO</td>\n",
       "      <td>Upper middle income</td>\n",
       "      <td>AO</td>\n",
       "      <td>-8.81155</td>\n",
       "      <td>IBRD</td>\n",
       "      <td>13.242</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Sub-Saharan Africa (all income levels)</td>\n",
       "      <td>21471618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>Europe &amp; Central Asia (developing only)</td>\n",
       "      <td>Tirane</td>\n",
       "      <td>ALB</td>\n",
       "      <td>Upper middle income</td>\n",
       "      <td>AL</td>\n",
       "      <td>41.3317</td>\n",
       "      <td>IBRD</td>\n",
       "      <td>19.8172</td>\n",
       "      <td>Albania</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>2897366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td></td>\n",
       "      <td>Andorra la Vella</td>\n",
       "      <td>AND</td>\n",
       "      <td>High income</td>\n",
       "      <td>AD</td>\n",
       "      <td>42.5075</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>1.5218</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>79218</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         adminregion       capitalCity iso3c  \\\n",
       "name                                                                           \n",
       "Aruba                                                       Oranjestad   ABW   \n",
       "Afghanistan                               South Asia             Kabul   AFG   \n",
       "Angola          Sub-Saharan Africa (developing only)            Luanda   AGO   \n",
       "Albania      Europe & Central Asia (developing only)            Tirane   ALB   \n",
       "Andorra                                               Andorra la Vella   AND   \n",
       "\n",
       "                     incomeLevel iso2c  latitude     lendingType longitude  \\\n",
       "name                                                                         \n",
       "Aruba                High income    AW   12.5167  Not classified  -70.0167   \n",
       "Afghanistan           Low income    AF   34.5228             IDA   69.1761   \n",
       "Angola       Upper middle income    AO  -8.81155            IBRD    13.242   \n",
       "Albania      Upper middle income    AL   41.3317            IBRD   19.8172   \n",
       "Andorra              High income    AD   42.5075  Not classified    1.5218   \n",
       "\n",
       "                    name                                         region  \\\n",
       "name                                                                      \n",
       "Aruba              Aruba  Latin America & Caribbean (all income levels)   \n",
       "Afghanistan  Afghanistan                                     South Asia   \n",
       "Angola            Angola         Sub-Saharan Africa (all income levels)   \n",
       "Albania          Albania      Europe & Central Asia (all income levels)   \n",
       "Andorra          Andorra      Europe & Central Asia (all income levels)   \n",
       "\n",
       "             (SP.POP.TOTL, 2013)  \n",
       "name                              \n",
       "Aruba                     102911  \n",
       "Afghanistan             30551674  \n",
       "Angola                  21471618  \n",
       "Albania                  2897366  \n",
       "Andorra                    79218  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "High income            80\n",
       "Upper middle income    53\n",
       "Lower middle income    51\n",
       "Low income             31\n",
       "dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso.incomeLevel.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "isoHash={}\n",
    "\n",
    "for r in iso.iterrows():\n",
    "#    print r[1][4],r[1][8]\n",
    "    isoHash[r[1][4]]=r[1][8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>node.geo N2:</td>\n",
       "      <td>SG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>node.geo N3:</td>\n",
       "      <td>SG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>node.geo N4:</td>\n",
       "      <td>SG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>node.geo N5:</td>\n",
       "      <td>IL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>node.geo N6:</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id country\n",
       "0  node.geo N2:      SG\n",
       "1  node.geo N3:      SG\n",
       "2  node.geo N4:      SG\n",
       "3  node.geo N5:      IL\n",
       "4  node.geo N6:      FR"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3min 9s, sys: 1.79 s, total: 3min 11s\n",
      "Wall time: 3min 9s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "replaceRe=re.compile(r'node.geo|:')\n",
    "df['idClean']=df.id.apply(lambda x:re.sub(replaceRe,'',x))\n",
    "#df['idClean']=df['idClean'].apply(lambda x:re.sub(':','',x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del df['id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>idClean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SG</td>\n",
       "      <td>N2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SG</td>\n",
       "      <td>N3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SG</td>\n",
       "      <td>N4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IL</td>\n",
       "      <td>N5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FR</td>\n",
       "      <td>N6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country idClean\n",
       "0      SG      N2\n",
       "1      SG      N3\n",
       "2      SG      N4\n",
       "3      IL      N5\n",
       "4      FR      N6"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Join the Dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "iso.index=iso.iso2c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 7.04 s, sys: 871 ms, total: 7.91 s\n",
      "Wall time: 7.91 s\n"
     ]
    }
   ],
   "source": [
    "%time df=df.join(iso,on='country')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Clean out Aggregates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df[df['incomeLevel']=='Aggregates']=None\n",
    "iso[iso['incomeLevel']=='Aggregates']=None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>idClean</th>\n",
       "      <th>adminregion</th>\n",
       "      <th>capitalCity</th>\n",
       "      <th>iso3c</th>\n",
       "      <th>incomeLevel</th>\n",
       "      <th>iso2c</th>\n",
       "      <th>latitude</th>\n",
       "      <th>lendingType</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>region</th>\n",
       "      <th>(SP.POP.TOTL, 2013)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SG</td>\n",
       "      <td>N2</td>\n",
       "      <td></td>\n",
       "      <td>Singapore</td>\n",
       "      <td>SGP</td>\n",
       "      <td>High income</td>\n",
       "      <td>SG</td>\n",
       "      <td>1.28941</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>103.85</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>5399200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SG</td>\n",
       "      <td>N3</td>\n",
       "      <td></td>\n",
       "      <td>Singapore</td>\n",
       "      <td>SGP</td>\n",
       "      <td>High income</td>\n",
       "      <td>SG</td>\n",
       "      <td>1.28941</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>103.85</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>5399200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SG</td>\n",
       "      <td>N4</td>\n",
       "      <td></td>\n",
       "      <td>Singapore</td>\n",
       "      <td>SGP</td>\n",
       "      <td>High income</td>\n",
       "      <td>SG</td>\n",
       "      <td>1.28941</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>103.85</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>5399200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IL</td>\n",
       "      <td>N5</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>ISR</td>\n",
       "      <td>High income</td>\n",
       "      <td>IL</td>\n",
       "      <td>31.7717</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>35.2035</td>\n",
       "      <td>Israel</td>\n",
       "      <td>Middle East &amp; North Africa (all income levels)</td>\n",
       "      <td>8059500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FR</td>\n",
       "      <td>N6</td>\n",
       "      <td></td>\n",
       "      <td>Paris</td>\n",
       "      <td>FRA</td>\n",
       "      <td>High income</td>\n",
       "      <td>FR</td>\n",
       "      <td>48.8566</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>2.35097</td>\n",
       "      <td>France</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>65920302</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country idClean adminregion capitalCity iso3c  incomeLevel iso2c latitude  \\\n",
       "0      SG      N2               Singapore   SGP  High income    SG  1.28941   \n",
       "1      SG      N3               Singapore   SGP  High income    SG  1.28941   \n",
       "2      SG      N4               Singapore   SGP  High income    SG  1.28941   \n",
       "3      IL      N5                           ISR  High income    IL  31.7717   \n",
       "4      FR      N6                   Paris   FRA  High income    FR  48.8566   \n",
       "\n",
       "      lendingType longitude       name  \\\n",
       "0  Not classified    103.85  Singapore   \n",
       "1  Not classified    103.85  Singapore   \n",
       "2  Not classified    103.85  Singapore   \n",
       "3  Not classified   35.2035     Israel   \n",
       "4  Not classified   2.35097     France   \n",
       "\n",
       "                                           region  (SP.POP.TOTL, 2013)  \n",
       "0         East Asia & Pacific (all income levels)              5399200  \n",
       "1         East Asia & Pacific (all income levels)              5399200  \n",
       "2         East Asia & Pacific (all income levels)              5399200  \n",
       "3  Middle East & North Africa (all income levels)              8059500  \n",
       "4       Europe & Central Asia (all income levels)             65920302  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>adminregion</th>\n",
       "      <th>capitalCity</th>\n",
       "      <th>iso3c</th>\n",
       "      <th>incomeLevel</th>\n",
       "      <th>iso2c</th>\n",
       "      <th>latitude</th>\n",
       "      <th>lendingType</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>region</th>\n",
       "      <th>(SP.POP.TOTL, 2013)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iso2c</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AW</th>\n",
       "      <td></td>\n",
       "      <td>Oranjestad</td>\n",
       "      <td>ABW</td>\n",
       "      <td>High income</td>\n",
       "      <td>AW</td>\n",
       "      <td>12.5167</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>-70.0167</td>\n",
       "      <td>Aruba</td>\n",
       "      <td>Latin America &amp; Caribbean (all income levels)</td>\n",
       "      <td>102911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AF</th>\n",
       "      <td>South Asia</td>\n",
       "      <td>Kabul</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Low income</td>\n",
       "      <td>AF</td>\n",
       "      <td>34.5228</td>\n",
       "      <td>IDA</td>\n",
       "      <td>69.1761</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>30551674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AO</th>\n",
       "      <td>Sub-Saharan Africa (developing only)</td>\n",
       "      <td>Luanda</td>\n",
       "      <td>AGO</td>\n",
       "      <td>Upper middle income</td>\n",
       "      <td>AO</td>\n",
       "      <td>-8.81155</td>\n",
       "      <td>IBRD</td>\n",
       "      <td>13.242</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Sub-Saharan Africa (all income levels)</td>\n",
       "      <td>21471618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>Europe &amp; Central Asia (developing only)</td>\n",
       "      <td>Tirane</td>\n",
       "      <td>ALB</td>\n",
       "      <td>Upper middle income</td>\n",
       "      <td>AL</td>\n",
       "      <td>41.3317</td>\n",
       "      <td>IBRD</td>\n",
       "      <td>19.8172</td>\n",
       "      <td>Albania</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>2897366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AD</th>\n",
       "      <td></td>\n",
       "      <td>Andorra la Vella</td>\n",
       "      <td>AND</td>\n",
       "      <td>High income</td>\n",
       "      <td>AD</td>\n",
       "      <td>42.5075</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>1.5218</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>79218</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   adminregion       capitalCity iso3c  \\\n",
       "iso2c                                                                    \n",
       "AW                                                    Oranjestad   ABW   \n",
       "AF                                  South Asia             Kabul   AFG   \n",
       "AO        Sub-Saharan Africa (developing only)            Luanda   AGO   \n",
       "AL     Europe & Central Asia (developing only)            Tirane   ALB   \n",
       "AD                                              Andorra la Vella   AND   \n",
       "\n",
       "               incomeLevel iso2c  latitude     lendingType longitude  \\\n",
       "iso2c                                                                  \n",
       "AW             High income    AW   12.5167  Not classified  -70.0167   \n",
       "AF              Low income    AF   34.5228             IDA   69.1761   \n",
       "AO     Upper middle income    AO  -8.81155            IBRD    13.242   \n",
       "AL     Upper middle income    AL   41.3317            IBRD   19.8172   \n",
       "AD             High income    AD   42.5075  Not classified    1.5218   \n",
       "\n",
       "              name                                         region  \\\n",
       "iso2c                                                               \n",
       "AW           Aruba  Latin America & Caribbean (all income levels)   \n",
       "AF     Afghanistan                                     South Asia   \n",
       "AO          Angola         Sub-Saharan Africa (all income levels)   \n",
       "AL         Albania      Europe & Central Asia (all income levels)   \n",
       "AD         Andorra      Europe & Central Asia (all income levels)   \n",
       "\n",
       "       (SP.POP.TOTL, 2013)  \n",
       "iso2c                       \n",
       "AW                  102911  \n",
       "AF                30551674  \n",
       "AO                21471618  \n",
       "AL                 2897366  \n",
       "AD                   79218  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#iso.index=iso.iso2c\n",
    "iso.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Get mapping of country name to income level\n",
    "# SG => High Income\n",
    "levelHash={}\n",
    "\n",
    "for r in iso.iterrows():\n",
    "#    print r[1][8]\n",
    "#    print r[1][8],r[1][3]\n",
    "    levelHash[r[1][8]]=r[1][3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#df['fullName']=df['country'].apply(lambda x:isoHash.get(x))\n",
    "#df['level']=df['country'].apply(lambda x:levelHash.get(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'High income'"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso[iso.iso2c=='GB'].incomeLevel.values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>country</th>\n",
       "      <th>idClean</th>\n",
       "      <th>adminregion</th>\n",
       "      <th>capitalCity</th>\n",
       "      <th>iso3c</th>\n",
       "      <th>incomeLevel</th>\n",
       "      <th>iso2c</th>\n",
       "      <th>latitude</th>\n",
       "      <th>lendingType</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>region</th>\n",
       "      <th>pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>node.geo N2:</td>\n",
       "      <td>SG</td>\n",
       "      <td>N2</td>\n",
       "      <td></td>\n",
       "      <td>Singapore</td>\n",
       "      <td>SGP</td>\n",
       "      <td>High income</td>\n",
       "      <td>SG</td>\n",
       "      <td>1.28941</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>103.85</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>5399200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>node.geo N3:</td>\n",
       "      <td>SG</td>\n",
       "      <td>N3</td>\n",
       "      <td></td>\n",
       "      <td>Singapore</td>\n",
       "      <td>SGP</td>\n",
       "      <td>High income</td>\n",
       "      <td>SG</td>\n",
       "      <td>1.28941</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>103.85</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>5399200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>node.geo N4:</td>\n",
       "      <td>SG</td>\n",
       "      <td>N4</td>\n",
       "      <td></td>\n",
       "      <td>Singapore</td>\n",
       "      <td>SGP</td>\n",
       "      <td>High income</td>\n",
       "      <td>SG</td>\n",
       "      <td>1.28941</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>103.85</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>5399200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>node.geo N5:</td>\n",
       "      <td>IL</td>\n",
       "      <td>N5</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>ISR</td>\n",
       "      <td>High income</td>\n",
       "      <td>IL</td>\n",
       "      <td>31.7717</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>35.2035</td>\n",
       "      <td>Israel</td>\n",
       "      <td>Middle East &amp; North Africa (all income levels)</td>\n",
       "      <td>8059500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>node.geo N6:</td>\n",
       "      <td>FR</td>\n",
       "      <td>N6</td>\n",
       "      <td></td>\n",
       "      <td>Paris</td>\n",
       "      <td>FRA</td>\n",
       "      <td>High income</td>\n",
       "      <td>FR</td>\n",
       "      <td>48.8566</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>2.35097</td>\n",
       "      <td>France</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>65920302</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id country idClean adminregion capitalCity iso3c  incomeLevel  \\\n",
       "0  node.geo N2:      SG      N2               Singapore   SGP  High income   \n",
       "1  node.geo N3:      SG      N3               Singapore   SGP  High income   \n",
       "2  node.geo N4:      SG      N4               Singapore   SGP  High income   \n",
       "3  node.geo N5:      IL      N5                           ISR  High income   \n",
       "4  node.geo N6:      FR      N6                   Paris   FRA  High income   \n",
       "\n",
       "  iso2c latitude     lendingType longitude       name  \\\n",
       "0    SG  1.28941  Not classified    103.85  Singapore   \n",
       "1    SG  1.28941  Not classified    103.85  Singapore   \n",
       "2    SG  1.28941  Not classified    103.85  Singapore   \n",
       "3    IL  31.7717  Not classified   35.2035     Israel   \n",
       "4    FR  48.8566  Not classified   2.35097     France   \n",
       "\n",
       "                                           region       pop  \n",
       "0         East Asia & Pacific (all income levels)   5399200  \n",
       "1         East Asia & Pacific (all income levels)   5399200  \n",
       "2         East Asia & Pacific (all income levels)   5399200  \n",
       "3  Middle East & North Africa (all income levels)   8059500  \n",
       "4       Europe & Central Asia (all income levels)  65920302  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' N2'"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.idClean.values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "levelValues=iso.incomeLevel.values\n",
    "levels=iso.incomeLevel.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "High income            80\n",
       "Upper middle income    53\n",
       "Lower middle income    51\n",
       "Low income             31\n",
       "dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso.incomeLevel.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "colourHash={}\n",
    "\n",
    "colours=sns.color_palette(\"dark\",n_colors=len(levels))\n",
    "\n",
    "for level, colour in zip(levels,colours):\n",
    "    if level:\n",
    "        colourHash[level]=colour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[u'High income' u'Low income' u'Upper middle income' u'Lower middle income']\n"
     ]
    }
   ],
   "source": [
    "print levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "counts=df.name.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Do we need this?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "perCapitaDf=pd.DataFrame(index=counts.index,data={'perCapita':counts.values})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>perCapita</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>7842269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>6049794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Korea, Rep.</th>\n",
       "      <td>2076298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>1656025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>1209704</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               perCapita\n",
       "United States    7842269\n",
       "China            6049794\n",
       "Korea, Rep.      2076298\n",
       "Germany          1656025\n",
       "Brazil           1209704"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perCapitaDf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "perCapitaDf=iso.join(perCapitaDf,on='name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "perCapitaDf.perCapita=perCapitaDf.perCapita/perCapitaDf['pop']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "iso['counts']=counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "perCapitaDf.sort(columns='perCapita',ascending=True,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>adminregion</th>\n",
       "      <th>capitalCity</th>\n",
       "      <th>iso3c</th>\n",
       "      <th>incomeLevel</th>\n",
       "      <th>iso2c</th>\n",
       "      <th>latitude</th>\n",
       "      <th>lendingType</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>region</th>\n",
       "      <th>pop</th>\n",
       "      <th>perCapita</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iso2c</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SG</th>\n",
       "      <td></td>\n",
       "      <td>Singapore</td>\n",
       "      <td>SGP</td>\n",
       "      <td>High income</td>\n",
       "      <td>SG</td>\n",
       "      <td>1.28941</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>103.85</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>5399200</td>\n",
       "      <td>0.015981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FI</th>\n",
       "      <td></td>\n",
       "      <td>Helsinki</td>\n",
       "      <td>FIN</td>\n",
       "      <td>High income</td>\n",
       "      <td>FI</td>\n",
       "      <td>60.1608</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>24.9525</td>\n",
       "      <td>Finland</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>5438972</td>\n",
       "      <td>0.016666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td></td>\n",
       "      <td>Amsterdam</td>\n",
       "      <td>NLD</td>\n",
       "      <td>High income</td>\n",
       "      <td>NL</td>\n",
       "      <td>52.3738</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>4.89095</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>16804432</td>\n",
       "      <td>0.017393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FR</th>\n",
       "      <td></td>\n",
       "      <td>Paris</td>\n",
       "      <td>FRA</td>\n",
       "      <td>High income</td>\n",
       "      <td>FR</td>\n",
       "      <td>48.8566</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>2.35097</td>\n",
       "      <td>France</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>65920302</td>\n",
       "      <td>0.017690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BM</th>\n",
       "      <td></td>\n",
       "      <td>Hamilton</td>\n",
       "      <td>BMU</td>\n",
       "      <td>High income</td>\n",
       "      <td>BM</td>\n",
       "      <td>32.3293</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>-64.706</td>\n",
       "      <td>Bermuda</td>\n",
       "      <td>North America</td>\n",
       "      <td>65001</td>\n",
       "      <td>0.019723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IS</th>\n",
       "      <td></td>\n",
       "      <td>Reykjavik</td>\n",
       "      <td>ISL</td>\n",
       "      <td>High income</td>\n",
       "      <td>IS</td>\n",
       "      <td>64.1353</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>-21.8952</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>323764</td>\n",
       "      <td>0.019872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LU</th>\n",
       "      <td></td>\n",
       "      <td>Luxembourg</td>\n",
       "      <td>LUX</td>\n",
       "      <td>High income</td>\n",
       "      <td>LU</td>\n",
       "      <td>49.61</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>6.1296</td>\n",
       "      <td>Luxembourg</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>543360</td>\n",
       "      <td>0.020092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td></td>\n",
       "      <td>Berlin</td>\n",
       "      <td>DEU</td>\n",
       "      <td>High income</td>\n",
       "      <td>DE</td>\n",
       "      <td>52.5235</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>13.4115</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>80645605</td>\n",
       "      <td>0.020535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SE</th>\n",
       "      <td></td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>SWE</td>\n",
       "      <td>High income</td>\n",
       "      <td>SE</td>\n",
       "      <td>59.3327</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>18.0645</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>9600379</td>\n",
       "      <td>0.024020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EE</th>\n",
       "      <td></td>\n",
       "      <td>Tallinn</td>\n",
       "      <td>EST</td>\n",
       "      <td>High income</td>\n",
       "      <td>EE</td>\n",
       "      <td>59.4392</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>24.7586</td>\n",
       "      <td>Estonia</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>1317997</td>\n",
       "      <td>0.024406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NO</th>\n",
       "      <td></td>\n",
       "      <td>Oslo</td>\n",
       "      <td>NOR</td>\n",
       "      <td>High income</td>\n",
       "      <td>NO</td>\n",
       "      <td>59.9138</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>10.7387</td>\n",
       "      <td>Norway</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>5079623</td>\n",
       "      <td>0.024667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td></td>\n",
       "      <td>Washington D.C.</td>\n",
       "      <td>USA</td>\n",
       "      <td>High income</td>\n",
       "      <td>US</td>\n",
       "      <td>38.8895</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>-77.032</td>\n",
       "      <td>United States</td>\n",
       "      <td>North America</td>\n",
       "      <td>316497531</td>\n",
       "      <td>0.024778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CH</th>\n",
       "      <td></td>\n",
       "      <td>Bern</td>\n",
       "      <td>CHE</td>\n",
       "      <td>High income</td>\n",
       "      <td>CH</td>\n",
       "      <td>46.948</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>7.44821</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>8089346</td>\n",
       "      <td>0.025378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT</th>\n",
       "      <td></td>\n",
       "      <td>Valletta</td>\n",
       "      <td>MLT</td>\n",
       "      <td>High income</td>\n",
       "      <td>MT</td>\n",
       "      <td>35.9042</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>14.5189</td>\n",
       "      <td>Malta</td>\n",
       "      <td>Middle East &amp; North Africa (all income levels)</td>\n",
       "      <td>423374</td>\n",
       "      <td>0.025939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LI</th>\n",
       "      <td></td>\n",
       "      <td>Vaduz</td>\n",
       "      <td>LIE</td>\n",
       "      <td>High income</td>\n",
       "      <td>LI</td>\n",
       "      <td>47.1411</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>9.52148</td>\n",
       "      <td>Liechtenstein</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>36925</td>\n",
       "      <td>0.026919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DK</th>\n",
       "      <td></td>\n",
       "      <td>Copenhagen</td>\n",
       "      <td>DNK</td>\n",
       "      <td>High income</td>\n",
       "      <td>DK</td>\n",
       "      <td>55.6763</td>\n",
       "      <td>Not classified</td>\n",
       "      <td>12.5681</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>5614932</td>\n",
       "      <td>0.030202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KR</th>\n",
       "      <td></td>\n",
       "      <td>Seoul</td>\n",
       "      <td>KOR</td>\n",
       "      <td>High income</td>\n",
       "      <td>KR</td>\n",
       "      <td>37.5323</td>\n",
       "      <td>IBRD</td>\n",
       "      <td>126.957</td>\n",
       "      <td>Korea, Rep.</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>50219669</td>\n",
       "      <td>0.041344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JG</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>CHI</td>\n",
       "      <td>High income</td>\n",
       "      <td>JG</td>\n",
       "      <td></td>\n",
       "      <td>Not classified</td>\n",
       "      <td></td>\n",
       "      <td>Channel Islands</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "      <td>162018</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NA</th>\n",
       "      <td>Sub-Saharan Africa (developing only)</td>\n",
       "      <td>Windhoek</td>\n",
       "      <td>NAM</td>\n",
       "      <td>Upper middle income</td>\n",
       "      <td>NA</td>\n",
       "      <td>-22.5648</td>\n",
       "      <td>IBRD</td>\n",
       "      <td>17.0931</td>\n",
       "      <td>Namibia</td>\n",
       "      <td>Sub-Saharan Africa (all income levels)</td>\n",
       "      <td>2303315</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TW</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>TWN</td>\n",
       "      <td>High income</td>\n",
       "      <td>TW</td>\n",
       "      <td></td>\n",
       "      <td>Not classified</td>\n",
       "      <td></td>\n",
       "      <td>Taiwan, China</td>\n",
       "      <td>East Asia &amp; Pacific (all income levels)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                adminregion      capitalCity iso3c  \\\n",
       "iso2c                                                                \n",
       "SG                                                 Singapore   SGP   \n",
       "FI                                                  Helsinki   FIN   \n",
       "NL                                                 Amsterdam   NLD   \n",
       "FR                                                     Paris   FRA   \n",
       "BM                                                  Hamilton   BMU   \n",
       "IS                                                 Reykjavik   ISL   \n",
       "LU                                                Luxembourg   LUX   \n",
       "DE                                                    Berlin   DEU   \n",
       "SE                                                 Stockholm   SWE   \n",
       "EE                                                   Tallinn   EST   \n",
       "NO                                                      Oslo   NOR   \n",
       "US                                           Washington D.C.   USA   \n",
       "CH                                                      Bern   CHE   \n",
       "MT                                                  Valletta   MLT   \n",
       "LI                                                     Vaduz   LIE   \n",
       "DK                                                Copenhagen   DNK   \n",
       "KR                                                     Seoul   KOR   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "JG                                                             CHI   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "...                                     ...              ...   ...   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NA     Sub-Saharan Africa (developing only)         Windhoek   NAM   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "TW                                                             TWN   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "NaN                                    None             None  None   \n",
       "\n",
       "               incomeLevel iso2c  latitude     lendingType longitude  \\\n",
       "iso2c                                                                  \n",
       "SG             High income    SG   1.28941  Not classified    103.85   \n",
       "FI             High income    FI   60.1608  Not classified   24.9525   \n",
       "NL             High income    NL   52.3738  Not classified   4.89095   \n",
       "FR             High income    FR   48.8566  Not classified   2.35097   \n",
       "BM             High income    BM   32.3293  Not classified   -64.706   \n",
       "IS             High income    IS   64.1353  Not classified  -21.8952   \n",
       "LU             High income    LU     49.61  Not classified    6.1296   \n",
       "DE             High income    DE   52.5235  Not classified   13.4115   \n",
       "SE             High income    SE   59.3327  Not classified   18.0645   \n",
       "EE             High income    EE   59.4392  Not classified   24.7586   \n",
       "NO             High income    NO   59.9138  Not classified   10.7387   \n",
       "US             High income    US   38.8895  Not classified   -77.032   \n",
       "CH             High income    CH    46.948  Not classified   7.44821   \n",
       "MT             High income    MT   35.9042  Not classified   14.5189   \n",
       "LI             High income    LI   47.1411  Not classified   9.52148   \n",
       "DK             High income    DK   55.6763  Not classified   12.5681   \n",
       "KR             High income    KR   37.5323            IBRD   126.957   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "JG             High income    JG            Not classified             \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "...                    ...   ...       ...             ...       ...   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NA     Upper middle income    NA  -22.5648            IBRD   17.0931   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "TW             High income    TW            Not classified             \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "NaN                   None  None      None            None      None   \n",
       "\n",
       "                  name                                          region  \\\n",
       "iso2c                                                                    \n",
       "SG           Singapore         East Asia & Pacific (all income levels)   \n",
       "FI             Finland       Europe & Central Asia (all income levels)   \n",
       "NL         Netherlands       Europe & Central Asia (all income levels)   \n",
       "FR              France       Europe & Central Asia (all income levels)   \n",
       "BM             Bermuda                                   North America   \n",
       "IS             Iceland       Europe & Central Asia (all income levels)   \n",
       "LU          Luxembourg       Europe & Central Asia (all income levels)   \n",
       "DE             Germany       Europe & Central Asia (all income levels)   \n",
       "SE              Sweden       Europe & Central Asia (all income levels)   \n",
       "EE             Estonia       Europe & Central Asia (all income levels)   \n",
       "NO              Norway       Europe & Central Asia (all income levels)   \n",
       "US       United States                                   North America   \n",
       "CH         Switzerland       Europe & Central Asia (all income levels)   \n",
       "MT               Malta  Middle East & North Africa (all income levels)   \n",
       "LI       Liechtenstein       Europe & Central Asia (all income levels)   \n",
       "DK             Denmark       Europe & Central Asia (all income levels)   \n",
       "KR         Korea, Rep.         East Asia & Pacific (all income levels)   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "JG     Channel Islands       Europe & Central Asia (all income levels)   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "...                ...                                             ...   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NA             Namibia          Sub-Saharan Africa (all income levels)   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "TW       Taiwan, China         East Asia & Pacific (all income levels)   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "NaN               None                                            None   \n",
       "\n",
       "             pop  perCapita  \n",
       "iso2c                        \n",
       "SG       5399200   0.015981  \n",
       "FI       5438972   0.016666  \n",
       "NL      16804432   0.017393  \n",
       "FR      65920302   0.017690  \n",
       "BM         65001   0.019723  \n",
       "IS        323764   0.019872  \n",
       "LU        543360   0.020092  \n",
       "DE      80645605   0.020535  \n",
       "SE       9600379   0.024020  \n",
       "EE       1317997   0.024406  \n",
       "NO       5079623   0.024667  \n",
       "US     316497531   0.024778  \n",
       "CH       8089346   0.025378  \n",
       "MT        423374   0.025939  \n",
       "LI         36925   0.026919  \n",
       "DK       5614932   0.030202  \n",
       "KR      50219669   0.041344  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "JG        162018        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "...          ...        ...  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NA       2303315        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "TW           NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "NaN          NaN        NaN  \n",
       "\n",
       "[70 rows x 12 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perCapitaDf.iloc[-70:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "finalDf=perCapitaDf.join(pd.DataFrame(counts,columns=['counts']),on='name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "finalDf.sort(columns='perCapita',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "finalDf=finalDf[~pd.isnull(finalDf.perCapita)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([               u'country',                u'idClean',\n",
       "                  u'adminregion',            u'capitalCity',\n",
       "                        u'iso3c',            u'incomeLevel',\n",
       "                        u'iso2c',               u'latitude',\n",
       "                  u'lendingType',              u'longitude',\n",
       "                         u'name',                 u'region',\n",
       "       (u'SP.POP.TOTL', u'2013')],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.loglog(finalDf['pop'].values,finalDf['counts'].values,'.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "countsHash=counts.to_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Plot AS Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "popHash=collections.OrderedDict()\n",
    "\n",
    "for row in iso.iterrows():\n",
    "#    print row[1]\n",
    "#    print row[1]['name'],row[1].values[-1]\n",
    "    \n",
    "    popHash[row[1]['name']]=row[1].values[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "212"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "counts=pd.DataFrame(data={'counts':counts.values,'pop':map(lambda x:popHash[x],counts.index.values)},index=counts.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "counts['countsPerCapita']=counts['counts']/counts['pop']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Plot Countries Sorted by ASs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../charts/as_count_10.png\n"
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   "source": [
    "counts.sort(columns='counts',inplace=True)\n",
    "\n",
    "topN=len(counts)\n",
    "topN=10\n",
    "direction=-1\n",
    "direction=1\n",
    "\n",
    "if not topN==counts.shape[0]:\n",
    "    setFigSize(dim=(15,4))\n",
    "else:\n",
    "    setFigSize(dim=(15,35))\n",
    "\n",
    "barList=plt.barh(range(topN),counts['counts'].values[::-1*direction][0:topN][::direction],0.8,log=True)\n",
    "trash=plt.yticks([r+0.4 for r in range(topN)],[c+' ('+replaceThousands(countsHash[c])+')' for nn,c in enumerate(counts.index[::direction][0:topN][::-1*direction])])\n",
    "\n",
    "if topN==counts.shape[0]:\n",
    "\n",
    "    for n,bar in enumerate(barList):\n",
    "        bar.set_color(colourHash[levelHash[counts.index[::direction][n][::-1*direction]]])\n",
    "#        print counts.index[n],popHash[counts.index[n]]\n",
    "    #    print counts.index[::-1][n],levelHash[counts.index[::-1][n]]\n",
    "    #sys.exit(1)\n",
    "    for n,(k,v) in enumerate(colourHash.items()):\n",
    "    #    print k,v\n",
    "        plt.annotate(k,xy=(0.05,0.91-(n*0.013)),xycoords='figure fraction',fontsize=24,color=v)\n",
    "\n",
    "plt.xlim(1,7842000)\n",
    "\n",
    "        \n",
    "if not topN==counts.shape[0]:\n",
    "    plt.savefig('../charts/as_count_'+str(topN)+'.png',dpi=200)\n",
    "    print '../charts/as_count_'+str(topN)+'.png'\n",
    "else:\n",
    "    plt.xticks([],[])\n",
    "    plt.tight_layout()\n",
    "    plt.savefig('../charts/as_count.png',dpi=200)   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Plot AS Per Capita"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "counts=counts[~(pd.isnull(counts.countsPerCapita))]\n",
    "# Clean out Taiwan, no population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "counts.sort(columns='countsPerCapita',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../charts/as_per_capita_count_10.png\n"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "topN=counts.shape[0]\n",
    "direction=-1\n",
    "\n",
    "topN=10\n",
    "\n",
    "if not topN==counts.shape[0]:\n",
    "    setFigSize(dim=(15,4))\n",
    "    isLog=False\n",
    "else:\n",
    "    setFigSize(dim=(15,35))\n",
    "    isLog=True\n",
    "\n",
    "barList=plt.barh(range(topN),counts.countsPerCapita.values[::-direction][0:topN][::-1*direction]\\\n",
    "                 ,0.8,log=isLog)\n",
    "trash=plt.yticks([r+0.5 for r in range(topN)],[c+' (%.2g)' % \\\n",
    "            (counts['countsPerCapita'].values[::-1*direction][0:topN][::-1*direction][n]) \\\n",
    "            for n,c in enumerate(counts.index[::-1*direction][0:topN][::-1*direction])])\n",
    "# +' ('+replaceThousands(countsHash[c])+')'\n",
    "for n,bar in enumerate(barList):\n",
    "#    print n, counts.index.values[::-1][n]\n",
    "    row=counts.irow(n)\n",
    "#    print row\n",
    "#    print levelHash[finalDf.index.values[::-1][n]]\n",
    "\n",
    "if topN==len(counts):\n",
    "\n",
    "    for n,bar in enumerate(barList[::-1]):\n",
    "        try:\n",
    "            '''\n",
    "            print counts.index[::direction][n]\n",
    "            print levelHash[counts.index[::direction][n]]\n",
    "            print colourHash[levelHash[counts.index[::direction][n]]]\n",
    "            print '-----'\n",
    "            '''\n",
    "            bar.set_color(colourHash[levelHash[counts.index[::direction][n]]])\n",
    "        except:\n",
    "            print 'ERROR'\n",
    "#        print counts.index[n],popHash[counts.index[n]]\n",
    "    #    print counts.index[::-1][n],levelHash[counts.index[::-1][n]]\n",
    "    #sys.exit(1)\n",
    "    for n,k in enumerate(['High income','Upper middle income','Lower middle income','Low income']):\n",
    "    #    print k,v\n",
    "        plt.annotate(k,xy=(0.05,0.91-(n*0.013)),xycoords='figure fraction',fontsize=24,color=colourHash[k])\n",
    "\n",
    "plt.xlabel('AS Count per Capita')\n",
    "plt.tight_layout()\n",
    "\n",
    "if not topN==len(counts):\n",
    "    plt.savefig('../charts/as_per_capita_count_'+str(topN)+'.png',dpi=200)\n",
    "    print '../charts/as_per_capita_count_'+str(topN)+'.png'\n",
    "else:\n",
    "    \n",
    "    plt.savefig('../charts/as_per_capita_count.png',dpi=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Now look at edges between countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "edgeFile=csv.reader(open('../data/midar-iff.links'),delimiter=' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "link L1:  N8888118:1.0.0.1 N120707 N120708 \r\n",
      "link L2:  N8888119:1.0.0.2 N120709 N120710 N106378 N120711 N120712 \r\n",
      "link L3:  N8888120:1.0.0.6 N106378 N120711 \r\n",
      "link L4:  N8888121:1.0.0.13 N120713 \r\n",
      "link L5:  N8888122:1.0.0.164 N120714 \r\n",
      "link L6:  N8888123:1.0.4.10 N120715 \r\n",
      "link L7:  N8888124:1.0.8.250 N120716 N120717 \r\n",
      "link L8:  N8888125:1.0.20.46 N120718 \r\n",
      "link L9:  N120718:1.0.24.22 N120719 \r\n",
      "link L10:  N8888126:1.0.24.150 N120720 \r\n",
      "link L11:  N699985:1.1.0.1 N120721 N120722 \r\n"
     ]
    }
   ],
   "source": [
    "!sed -n 1530,1540p ../data/midar-iff.links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 56min 24s, sys: 22.7 s, total: 56min 46s\n",
      "Wall time: 56min 12s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "nodeGeoHash=collections.OrderedDict()\n",
    "# Node #X=>country Y\n",
    "\n",
    "for r in df.iterrows():\n",
    "#    print r[1][1],r[1][2]\n",
    "    nodeGeoHash[r[1][2]]=r[1][1]\n",
    "#    sys.exit(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "edgeCounter=collections.Counter()\n",
    "ipCounter=collections.Counter()\n",
    "\n",
    "#nodeGeoHash={}\n",
    "# Figure out how to populate this later\n",
    "\n",
    "for line in edgeFile:\n",
    "    if not re.search(r'#',line[0]):\n",
    "#        print line\n",
    "        source=line[3].partition(':')[0]\n",
    "#        print source\n",
    "#        print nodeGeoHash.get(source)\n",
    "#        print line[4:-1]\n",
    "        \n",
    "        for dest in line[4:-1]:\n",
    "            edgeCounter[(nodeGeoHash.get(source),nodeGeoHash.get(dest))]+=1\n",
    "\n",
    "        ipCounter[source]+=1\n",
    "        # Count number of IPs associated with each AS\n",
    "        \n",
    "#        sys.exit(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for k,v in edgeCounter.most_common():\n",
    "    if not k[0]==k[1] and k[0] and k[1]:\n",
    "        print k,v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# version: $Id: kapar.cc,v 1.162 2012/03/14 00:24:54 kkeys Exp $\r\n",
      "# version: $Id: PathLoader.cc,v 1.19 2012/01/04 20:44:46 kkeys Exp $\r\n",
      "# start time: 1367051656 (2013-04-27 01:34:16 PDT)\r\n",
      "# command line: /home/kkeys/WIP/topology/archipelago/aliasResolution/midar/../kapar/kapar -il -py -r31 -sir -c0.5 -nv -adms -d1 -mn -lb -1a -oals -O /scratch/alias-resolution/run-20130422/kapar/midar-iff -z 24\r\n",
      "#   -B /scratch/alias-resolution/run-20130422/bogon-bn-agg-20130422.txt\r\n",
      "#   -A /scratch/alias-resolution/run-20130422/kapar/midar-iff.pairs\r\n",
      "#   -P /san5/topology/ark/data/team-probing/list-7.allpref24/team-1/daily/2013/cycle-20130407/daily.l7.t1.c002462.20130407.ams3-nl.warts.gz\r\n",
      "#   -P /san5/topology/ark/data/team-probing/list-7.allpref24/team-1/daily/2013/cycle-20130407/daily.l7.t1.c002462.20130407.amw-us.warts.gz\r\n",
      "#   -P /san5/topology/ark/data/team-probing/list-7.allpref24/team-1/daily/2013/cycle-20130407/daily.l7.t1.c002462.20130407.bcn-es.warts.gz\r\n",
      "#   -P /san5/topology/ark/data/team-probing/list-7.allpref24/team-1/daily/2013/cycle-20130407/daily.l7.t1.c002462.20130407.bed-us.warts.gz\r\n"
     ]
    }
   ],
   "source": [
    "!head ../data/midar-iff.links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nodesDf=pd.read_csv('../data/midar-iff.nodes_count',delimiter='  ',header=False,names=['id','n'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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    "nodesDf['country']=nodesDf['id'].apply(lambda x:nodeGeoHash.get(x))"
   ]
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  {
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   "metadata": {
    "collapsed": false
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    "collapsed": false
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   "source": [
    "groups=nodesDf.groupby('country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "aggregated=groups.agg(np.sum)"
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  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>23600900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CN</th>\n",
       "      <td>18204066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KR</th>\n",
       "      <td>6239463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>4978297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BR</th>\n",
       "      <td>3633394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FR</th>\n",
       "      <td>3503206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JP</th>\n",
       "      <td>2819883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GB</th>\n",
       "      <td>2417173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ES</th>\n",
       "      <td>2182683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MX</th>\n",
       "      <td>1954976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RU</th>\n",
       "      <td>1866683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT</th>\n",
       "      <td>1846304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IN</th>\n",
       "      <td>1846252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>1313782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TW</th>\n",
       "      <td>1234726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>913979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>881191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PL</th>\n",
       "      <td>874025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SE</th>\n",
       "      <td>694608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>684384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>618688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CH</th>\n",
       "      <td>617070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RO</th>\n",
       "      <td>574582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TR</th>\n",
       "      <td>522776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DK</th>\n",
       "      <td>511596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>484731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TH</th>\n",
       "      <td>472070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SA</th>\n",
       "      <td>466732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT</th>\n",
       "      <td>452039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EG</th>\n",
       "      <td>413541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SR</th>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PM</th>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CK</th>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YT</th>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MF</th>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SO</th>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ST</th>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CF</th>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ER</th>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KI</th>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NR</th>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SH</th>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AQ</th>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SS</th>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TD</th>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GW</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KP</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NF</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NU</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TV</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SX</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CC</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PN</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UM</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GS</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IO</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BL</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CX</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TK</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TF</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>248 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                n\n",
       "country          \n",
       "US       23600900\n",
       "CN       18204066\n",
       "KR        6239463\n",
       "DE        4978297\n",
       "BR        3633394\n",
       "FR        3503206\n",
       "JP        2819883\n",
       "GB        2417173\n",
       "ES        2182683\n",
       "MX        1954976\n",
       "RU        1866683\n",
       "IT        1846304\n",
       "IN        1846252\n",
       "CA        1313782\n",
       "TW        1234726\n",
       "AR         913979\n",
       "NL         881191\n",
       "PL         874025\n",
       "SE         694608\n",
       "UA         684384\n",
       "AU         618688\n",
       "CH         617070\n",
       "RO         574582\n",
       "TR         522776\n",
       "DK         511596\n",
       "CO         484731\n",
       "TH         472070\n",
       "SA         466732\n",
       "PT         452039\n",
       "EG         413541\n",
       "...           ...\n",
       "SR            122\n",
       "PM            114\n",
       "CK            111\n",
       "YT            105\n",
       "MF            105\n",
       "SO            102\n",
       "ST            102\n",
       "CF             75\n",
       "ER             63\n",
       "KI             63\n",
       "NR             60\n",
       "SH             53\n",
       "AQ             42\n",
       "SS             42\n",
       "TD             39\n",
       "GW             30\n",
       "KP             27\n",
       "NF             21\n",
       "NU             21\n",
       "TV             18\n",
       "SX             15\n",
       "CC             15\n",
       "PN             12\n",
       "UM             12\n",
       "GS             12\n",
       "IO             12\n",
       "BL             12\n",
       "CX              9\n",
       "TK              9\n",
       "TF              3\n",
       "\n",
       "[248 rows x 1 columns]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregated.sort('n',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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